{"id":"https://openalex.org/W7160300716","doi":"https://doi.org/10.1111/tgis.70274","title":"Predicting Origin\u2013Destination Travel Flow Based on a Spatiotemporal Relational Graph Learning Approach","display_name":"Predicting Origin\u2013Destination Travel Flow Based on a Spatiotemporal Relational Graph Learning Approach","publication_year":2026,"publication_date":"2026-05-01","ids":{"openalex":"https://openalex.org/W7160300716","doi":"https://doi.org/10.1111/tgis.70274"},"language":"en","primary_location":{"id":"doi:10.1111/tgis.70274","is_oa":false,"landing_page_url":"https://doi.org/10.1111/tgis.70274","pdf_url":null,"source":{"id":"https://openalex.org/S859791518","display_name":"Transactions in GIS","issn_l":"1361-1682","issn":["1361-1682","1467-9671"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions in GIS","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135348158","display_name":"Yan Shi","orcid":"https://orcid.org/0000-0002-9136-9764"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]},{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Shi","raw_affiliation_strings":["Department of Geo\u2010Informatics Central South University  Changsha China","Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural Resources  Shenzhen China"],"raw_orcid":"https://orcid.org/0000-0002-9136-9764","affiliations":[{"raw_affiliation_string":"Department of Geo\u2010Informatics Central South University  Changsha China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural Resources  Shenzhen China","institution_ids":["https://openalex.org/I211433327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135337881","display_name":"Yixun Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixun Liu","raw_affiliation_strings":["Department of Geo\u2010Informatics Central South University  Changsha China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geo\u2010Informatics Central South University  Changsha China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037781729","display_name":"D Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]},{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Da Wang","raw_affiliation_strings":["College of Electronic Science and Technology National University of Defense Technology  Changsha China","Department of Geo\u2010Informatics Central South University  Changsha China"],"raw_orcid":"https://orcid.org/0000-0003-0428-5982","affiliations":[{"raw_affiliation_string":"College of Electronic Science and Technology National University of Defense Technology  Changsha China","institution_ids":["https://openalex.org/I170215575"]},{"raw_affiliation_string":"Department of Geo\u2010Informatics Central South University  Changsha China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135389026","display_name":"Min Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Deng","raw_affiliation_strings":["Department of Geo\u2010Informatics Central South University  Changsha China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geo\u2010Informatics Central South University  Changsha China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5135366671","display_name":"Rui Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I198357462","display_name":"Changsha University","ror":"https://ror.org/011d8sm39","country_code":"CN","type":"education","lineage":["https://openalex.org/I198357462"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Jin","raw_affiliation_strings":["School of Architecture and Planning Hunan University  Changsha China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Architecture and Planning Hunan University  Changsha China","institution_ids":["https://openalex.org/I198357462"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5037781729"],"corresponding_institution_ids":["https://openalex.org/I139660479","https://openalex.org/I170215575"],"apc_list":{"value":3450,"currency":"USD","value_usd":3450},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.48908963,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.4659000039100647,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.4659000039100647,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.450300008058548,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11942","display_name":"Transportation and Mobility Innovations","score":0.014800000004470348,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5838000178337097},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.453900009393692},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.39399999380111694},{"id":"https://openalex.org/keywords/travel-time","display_name":"Travel time","score":0.3580999970436096},{"id":"https://openalex.org/keywords/statistical-relational-learning","display_name":"Statistical relational learning","score":0.3452000021934509},{"id":"https://openalex.org/keywords/flow-network","display_name":"Flow network","score":0.3402000069618225},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.3312999904155731}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6869000196456909},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5838000178337097},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5325000286102295},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.453900009393692},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.39399999380111694},{"id":"https://openalex.org/C2985733770","wikidata":"https://www.wikidata.org/wiki/Q1233007","display_name":"Travel time","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.3452000021934509},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.3312999904155731},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31869998574256897},{"id":"https://openalex.org/C40207289","wikidata":"https://www.wikidata.org/wiki/Q755662","display_name":"Relational model","level":3,"score":0.3091999888420105},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3075999915599823},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2858000099658966},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.2606000006198883},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2556000053882599}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1111/tgis.70274","is_oa":false,"landing_page_url":"https://doi.org/10.1111/tgis.70274","pdf_url":null,"source":{"id":"https://openalex.org/S859791518","display_name":"Transactions in GIS","issn_l":"1361-1682","issn":["1361-1682","1467-9671"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions in GIS","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6561380415","display_name":null,"funder_award_id":"CX20250270","funder_id":"https://openalex.org/F4320326217","funder_display_name":"Hunan Provincial Innovation Foundation for Postgraduate"},{"id":"https://openalex.org/G694004821","display_name":null,"funder_award_id":"42371477","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326217","display_name":"Hunan Provincial Innovation Foundation for Postgraduate","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W2047332899","https://openalex.org/W2183679353","https://openalex.org/W2292548112","https://openalex.org/W2535394993","https://openalex.org/W2589220953","https://openalex.org/W2604314403","https://openalex.org/W2612169332","https://openalex.org/W2623357190","https://openalex.org/W2802508687","https://openalex.org/W2803614648","https://openalex.org/W2898652385","https://openalex.org/W2901504064","https://openalex.org/W2903871660","https://openalex.org/W2910892140","https://openalex.org/W2924028299","https://openalex.org/W2946160394","https://openalex.org/W2972093239","https://openalex.org/W2972461593","https://openalex.org/W3029978369","https://openalex.org/W3040626849","https://openalex.org/W3049690032","https://openalex.org/W3109254449","https://openalex.org/W3128993782","https://openalex.org/W3135093357","https://openalex.org/W3135400423","https://openalex.org/W3149135218","https://openalex.org/W3157768256","https://openalex.org/W3194196251","https://openalex.org/W3204365986","https://openalex.org/W3207778928","https://openalex.org/W3210458411","https://openalex.org/W3216320999","https://openalex.org/W4220881233","https://openalex.org/W4223541767","https://openalex.org/W4225157025","https://openalex.org/W4226288807","https://openalex.org/W4281285792","https://openalex.org/W4283211784","https://openalex.org/W4296311966","https://openalex.org/W4378805108","https://openalex.org/W4382239616","https://openalex.org/W4387476873","https://openalex.org/W4388936714","https://openalex.org/W4390905463","https://openalex.org/W4399039951","https://openalex.org/W4399975443","https://openalex.org/W4406632683","https://openalex.org/W4408544830","https://openalex.org/W4412807346","https://openalex.org/W4415532687"],"related_works":[],"abstract_inverted_index":{"ABSTRACT":[0],"Accurate":[1],"prediction":[2],"of":[3,35,155,200],"origin\u2013destination":[4],"(OD)":[5],"travel":[6,25,67,94,109,172,179],"flow":[7,26,95],"is":[8,128,148],"essential":[9],"for":[10,92],"location\u2010based":[11],"services":[12],"such":[13,55],"as":[14,38,56],"traffic":[15],"management,":[16],"ride\u2010hailing":[17],"dispatch,":[18],"and":[19,48,59,115,118,135],"emergency":[20],"response.":[21],"However,":[22],"forecasting":[23],"OD":[24,66,93,171],"presents":[27],"greater":[28],"challenges":[29],"than":[30],"estimating":[31],"inflows":[32],"or":[33],"outflows":[34],"individual":[36],"regions,":[37],"it":[39],"requires":[40],"modeling":[41],"complex":[42],"spatiotemporal":[43,123],"dependencies":[44,137],"between":[45],"both":[46],"origin":[47,114],"destination":[49,116],"regions":[50],"simultaneously.":[51],"Furthermore,":[52],"external":[53,156],"factors":[54],"weather":[57],"conditions":[58],"calendar":[60],"dates":[61],"exert":[62],"heterogeneous":[63,153],"influences":[64],"on":[65,176],"flow,":[68],"yet":[69],"these":[70,80,139],"are":[71,161],"rarely":[72],"adequately":[73],"incorporated":[74],"in":[75,203],"existing":[76],"approaches.":[77],"To":[78],"address":[79],"issues,":[81],"this":[82],"paper":[83],"proposes":[84],"a":[85,165],"SpatioTemporal":[86],"Relational":[87],"Graph":[88],"Learning":[89],"(STRGL)":[90],"model":[91,105,133],"prediction.":[96],"Our":[97],"framework":[98],"first":[99],"constructs":[100],"four":[101],"relational":[102,124,140],"graphs":[103],"to":[104,131,150,168],"multiple":[106,186],"relationships":[107],"among":[108],"flows,":[110],"including":[111],"spatial":[112,134],"distribution,":[113],"semantics,":[117],"temporal":[119,136],"fluctuation":[120],"patterns.":[121],"A":[122],"graph":[125],"convolutional":[126],"network":[127],"then":[129],"employed":[130],"jointly":[132],"across":[138,190],"graphs.":[141],"Additionally,":[142],"an":[143],"attention\u2010based":[144],"environmental":[145],"feature\u2010learning":[146],"module":[147],"designed":[149],"quantify":[151],"the":[152,198,204],"effects":[154],"factors.":[157],"The":[158],"learned":[159],"representations":[160],"finally":[162],"decoded":[163],"by":[164],"multilayer":[166],"perceptron":[167],"predict":[169],"future":[170],"flows.":[173],"Extensive":[174],"experiments":[175],"two":[177],"real\u2010world":[178],"datasets":[180],"show":[181],"that":[182],"STRGL":[183,206],"consistently":[184],"outperforms":[185],"state\u2010of\u2010the\u2010art":[187],"baseline":[188],"methods":[189],"most":[191],"evaluation":[192],"metrics.":[193],"Ablation":[194],"studies":[195],"further":[196],"validate":[197],"contribution":[199],"each":[201],"component":[202],"proposed":[205],"framework.":[207]},"counts_by_year":[],"updated_date":"2026-06-18T08:10:14.011955","created_date":"2026-05-06T00:00:00"}
